Ancestral Genome Reconstruction in Bacteria

The rapid accumulation of numerous sequenced genomes has provided a golden opportunity for ancestral state reconstruction studies, especially in the whole genome reconstruction area. However, most ancestral genome reconstruction methods developed so far only focus on gene or replicon sequences instead of whole genomes. They rely largely on either detailed modeling of evolutionary events or edit distance computation, both of which can be computationally prohibitive for large data sets. Hence, most of these methods can only be applied to a small number of features and species. In this dissertation, we describe the design, implementation, and evaluation of an ancestral genome reconstruction system (REGEN) for bacteria. It is the first bacterial genome reconstruction tool that focuses on ancestral state reconstruction at the genome scale instead of the gene scale. It not only reconstructs ancestral gene content and contiguous gene runs using either a maximum parsimony or a maximum likelihood criterion but also replicon structures of each ancestor. Based on the reconstructed genomes, it can infer all major events at both the gene scale, such as insertion, deletion, and translocation, and the replicon scale, such as replicon gain, loss, and merge. REGEN finishes by producing a visual representation of the entire evolutionary history of all genomes in the study. With a model-free reconstruction method at its core, the computational requirement for ancestral genome reconstruction is reduced sufficiently for the tool to be applied to large data sets with dozens of genomes and thousands of features. To achieve as accurate a